Modern transport infrastructures need to be able to cope with growing, and increasingly mobile, populations, yet central and local governments are operating in an era of austerity where major new investment in infrastructure is unlikely. Data science and data-centric engineering offer a potential solution to this problem. By optimising the existing use of infrastructure through exploitation of new data about the way the infrastructure is used, there is the possibility of improving the performance of existing traffic networks without making major new investments.
Explaining the science
The availability of new data is transforming the way we study human behaviour as well as plan and operate infrastructure. Along with data from sensors there have also been great increases in crowd-sourced data, social data, and administrative data. Millions of volunteers contribute geographic data to platforms like OpenStreetMap capturing details including points of interest, bus stops, restaurants, and walking trails.
At the same time, huge swaths of social data (e.g., online reviews, posts on social networking sites, etc.) augment our physical space with additional data that can reveal commuting patterns and other human activity.
Finally, administrative and government processes are digital, available in real-time, and more easily linked and searched than ever before.
This project seeks to investigate how the additional data sources detailed above complement sensor and mobile phone data to give us a deeper understanding of human behaviour. This understanding will then be used to improve modelling and prediction tasks.
The project also seeks to innovate ways in which to visualise and analyse relevant data quickly.
The project is operating in collaboration with the Oxfordshire County Council and Google’s Better Cities programme. As a medieval city with a historic, unplanned centre, Oxford faces a number of infrastructure challenges as its 160,000 residents and nearly 50,000 inward commuters move around the city.
In the last few years Oxford has opened a new rail station, engaged in a large commercial redevelopment project in its city centre, and experienced multiple instances of severe flooding.
Through the data and methods developed in this project, we will better forecast traffic disruptions and understand how changes in infrastructure and business redevelopment affect mobility.